Survival prediction and variable selection with simultaneous shrinkage and grouping priors

DOI10.1002/SAM.11266OpenAlexW1677432275MaRDI QIDQ4969996

No author found.

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.11266

zbMATH Keywords

group LassomicroarraysBayesian variable selectionelastic netCox proportional hazards modelBayesian Lassofused Lasso

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (5)

VARIABLE SELECTION FOR BAYESIAN SURVIVAL MODELS USING BREGMAN DIVERGENCE MEASURE ⋮ Variable selection for high-dimensional genomic data with censored outcomes using group Lasso prior ⋮ Identification of survival relevant genes with measurement error in gene expression incorporated ⋮ An exact sampler for fully Baysian elastic net ⋮ Bayesian survival analysis using gamma processes with adaptive time partition

Uses Software

• Unnamed Item
• AS 136
• uniCox

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Algorithm AS 136: A K-Means Clustering Algorithm
• Principled sure independence screening for Cox models with ultra-high-dimensional covariates
• Inferring metabolic networks using the Bayesian adaptive graphical Lasso with informative priors
• A cocktail algorithm for solving the elastic net penalized Cox's regression in high dimensions
• The Bayesian elastic net
• Penalized regression, standard errors, and Bayesian Lassos
• Univariate Shrinkage in the Cox Model for High Dimensional Data
• An efficient computational approach for prior sensitivity analysis and cross‐validation
• The Bayesian Lasso
• Hierarchically penalized Cox regression with grouped variables
• Partial likelihood
• Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
• Bayesian Information Criterion for Censored Survival Models
• Sparsity and Smoothness Via the Fused Lasso
• Regularization and Variable Selection Via the Elastic Net
• The dantzig selector for censored linear regression models
• Model Selection and Estimation in Regression with Grouped Variables
• Empirical Bayes Gibbs sampling
• Bayesian Variable Selection in Clustering High-Dimensional Data
• Prediction by Supervised Principal Components

This page was built for publication: Survival prediction and variable selection with simultaneous shrinkage and grouping priors